Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T23:01:00.152995Z
Paper Citation Record · LEDGER
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation
As of 11 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2508.06115.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
7 of 7 outbound references displayed
- verified exact0
- verified fuzzy3
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 36bc6288-ca71-42f4-aff0-b18bb954c936 · outbound
This paper cites In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 989–998.
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 989–998
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T23:01:00.332156Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation afc4ab36-8eee-4256-8545-e5aff4ebe507 · outbound
This paper cites A Brief Survey and an Application of Semantic Image Segmentation for Autonomous Driving.
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation A Brief Survey and an Application of Semantic Image Segmentation for Autonomous Driving
Reference 7
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T23:01:00.210069Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4226ce3c-a617-4c06-b7a4-cdb0e98e0a0f · outbound
This paper cites Exploring Simple Open-Vocabulary Semantic Segmentation.
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation Exploring Simple Open-Vocabulary Semantic Segmentation
Reference 2016
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:01:00.108557Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56413fac-9e7e-4d3f-84a1-11cbf214d70e · outbound
This paper cites Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts.
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:01:00.098365Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ebbd834-0513-4f36-a63e-7abfcabe6308 · outbound
This paper cites Training-Free Semantic Segmentation via LLM-Supervision.
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation Training-Free Semantic Segmentation via LLM-Supervision
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:01:00.114920Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae18c143-6a61-4d1a-bc75-6bc5dfc23e38 · outbound
This paper cites In Ad- vances in Neural Information Processing Systems.
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation In Ad- vances in Neural Information Processing Systems
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T23:01:00.304224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4400cd2b-47b6-49f5-a118-ee58770d6c8a · outbound
This paper cites In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 26794–26803.
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 26794–26803
Reference 2024
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T23:01:00.348278Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Pith citing papers
No inbound Pith citation observations are available.